code: def create_initialiser(F, EF, apply_scale=True, use_normal_ABCD=True):
      """
      Created an RCE initialiser with a specified F and expected value of F over
      D. F should be a function of A, B, C, D and EF should be a function of A,
      B, C.
  
      Args:
          F (function):
          EF (function):
          apply_scale (Bool): Apply scaling to mean and variance
          use_normal_ABCD (Bool): True to use Gaussian rvs for A, B, C, D .
              This is valid by the inverse transform theorem.
      """
  
      class LambdaRceInitialiser(RceInitialiser):
          """
          RceInitialiser that allows _F and _expected_over_D_of_F to be defined
          with lambda functions.
          """
  
          def __init__(self):
              super().__init__(apply_scale, use_normal_ABCD)
              self._F = F
              self._expected_over_D_of_F = EF
  
      return LambdaRceInitialiser()
  
imports: import numpy
  import abc
  from scipy.stats import gennorm
  from scipy.special import gamma
  from scipy.stats import laplace
label_desc: Use image node_id 1 for calling a global function with example usage: create_initialiser(F, EF, apply_scale, use_normal_ABCD) and returns: LambdaRceInitialiser